ICOS Science Conference 2020, Session 1

1. Improved understanding of urban street
tree and soil carbon cycle
Minttu Havu1
, Anu Riikonen3
, Liisa Kulmala2,3
, and Leena Järvi1,4
1
Institute for Atmospheric and Earth System Research /Physics, University of Helsinki, Finland.
2
Finnish Meteorological Institute, Helsinki, Finland.
3
Institute for Atmospheric and Earth System Research /Forest, University of Helsinki, Finland.
4
Helsinki Institute of Sustainability Science, University of Helsinki, Finland.
Email: minttu.havu@helsinki.fi
15/09/2020

2. 2
Introduction
➢ Cities strive for carbon neutrality, therefore, policy-
making requires knowledge of how to maximize urban
biogenic carbon sequestration
➢ Identifying the magnitude of the effect of vegetation
and soil on the carbon cycle in urban areas can reduce
the uncertainty of anthropogenic emissions determined
from satellite or atmospheric in-situ observations
➢ The effect of vegetation and soil on the carbon cycle is
easily overshadowed by human emissions in urban
areas and is challenging to evaluate
➢ In order to provide more advanced models, this study
focuses on the development and evaluation of the
urban land surface model SUEWS and the soil carbon
model Yasso, using measurements from urban street
trees and soil from Helsinki
Minttu Havu15/09/2020

3. 3
Measurements from two test streets in
Helsinki are used in the model evaluation
➢ Carbon and water fluxes and pools have been
monitored in two streets with two tree species (Alnus
glutinosa and Tilia x Vulgaris) in 2002-2014
Figure 1. The measurement sites and modelling areas in Helsinki are
located on two streets (©Kaupunkimittausosasto 2019, Helsinki, Finland)
Measurements
Test streets
• Sap flow
• Soil water content
• Loss-on-ignition based
soil carbon stock
• Leaf-level photosynthesis
Background
meteorology
• Precipitation
• Air pressure
• Air temperature
• Solar radiation
• Wind speed
• Relative Humidity
Figure 2. Measurements from the test street
Minttu Havu15/09/2020

4. 4
➢ The Surface Urban Energy and Water Balance
Scheme (Järvi et al. 2019)
➢ Simulates the urban radiation, energy and water
balances, and carbon dioxide exchange with
meteorological variables and surface characteristics
CO2
exchange added to urban land
surface model SUEWS
➢ Biogenic components
➢
CO2
uptake is estimated with empirical canopy-level model
➢
Respiration is estimated with its exponential dependence
on temperature
Figure 3. The seven surface types in SUEWS (Ward et al., 2016)
GPP = βmax
LAI g(K↓
) g(Δq) g(Tair
) g(Δθ)
RES = max(a exp(Tair
b), 0.6)
Figure 4. The dependence of soil
respiration (Fsoil
) on daily air
temperature. The fit with a black
line (Järvi et al., 2012)
GPP = Gross primary production
βmax
= Maximum carbon uptake
LAI = Leaf area index
K↓
= Incoming shortwave
radiation
Δq = specific humidity deficit
Tair
= air temperature
Δθ = soil moisture deficit
a, b = fitted parameters
Minttu Havu15/09/2020

5. 5
The soil carbon model
Yasso
➢ The soil carbon decomposition model Yasso15 simulates
the stock and the annual changes of soil carbon, and
heterotrophic soil respiration (Järvenpää et al., 2020)
➢ Litter is divided to five compartments based on their
chemical composition
➢ Decomposition rates depend on temperature and
moisture
➢ Previous research mostly in forest and agricultural soils
Figure 5. The flow chart of Yasso model. The boxes are
the compartments and the arrows are carbon fluxes
(Repo et al., 2016)
Minttu Havu15/09/2020

6. 6
Carbon uptake and evapotranspiration
are determined by surface conductance
➢ Surface (stomatal) conductance depends on air
temperature, specific humidity, soil moisture and
shortwave radiation
➢ Previously, the functions were fitted against eddy
covariance measurements
Figure 6. Relations for the dependence of surface conductance (g) on environmental factors
for this study (red) and from Ward et al., 2016 (black)
➢ In this study, the functions are fitted against leaf-level
photosynthesis measurements (scaled to canopy level)
➢ Background meteorology from Helsinki and local soil
moisture measurements are used to fit street trees
➢ The potential carbon uptake is determined
Minttu Havu15/09/2020

7. 7
Evaluating modelled evapotranspiration
with sap flow measurements
Figure 8. Diurnal cycles of modelled street tree evaporation (blue line)
and measured sap flow (black line) averaged over summer 2011
Figure 7. Correlation between the measured sap flow
and modelled evaporation in summer 2011
➢ Comparison between modelled evapotranspiration (from
now on evaporation) from trees and measured sap flow
from summer 2011
➢ SUEWS overestimates the evaporation from trees
Minttu Havu15/09/2020

8. 8
Simulated CO2
uptake and respiration
➢ New parameters for street trees increase
the amount of carbon uptake compared to
previous study made in Helsinki (Järvi et al.,
2019)
Figure 9. Modelled diurnal cycles of street tree photosynthetic carbon uptake (solid
red line), respiration (dashed red line) and their combination (black line) averaged
over summer 2011
Minttu Havu15/09/2020

9. 9
Evaluating Yasso in street soils
Figure 10. Modelled (black) and measured (red) average carbon stock in soil (±SD) for Norkkokuja (left) and Pausterinkatu (right) streets
➢ The soil carbon decomposition depends on temperature,
precipitation and soil type
➢ Two test streets were constructed in 2002 and soil carbon
stocks were monitored until 2014
➢ The modelled annual soil carbon stock is evaluated against
loss-on-ignition based soil carbon measurements from streets
➢ Yasso is able to model the initial carbon loss and its
subsequent stabilization
Minttu Havu15/09/2020

10. 10
Conclusions
➢ The measurements from urban streets in Helsinki are used to evaluate the urban vegetation and soil carbon models
➢ The surface conductance model in SUEWS was parameterized with photosynthesis measurements
➢ The performance of stomatal conductance model was evaluated with how well the modelled evaporation compared
against sap flow measurements from the street trees
➢ The soil carbon stock simulated by Yasso was evaluated with soil carbon measurements for the first time in urban areas
References
Järvenpää, M., Repo, A., Akujärvi, A., Kaasalainen, M. & Liski, J. (2020). Soil carbon model Yasso15 - Bayesian calibration using worldwide litter
decomposition and carbon stock data. Manuscript in preparation.
Järvi, L., Nordbo, A., Junninen, H., Riikonen, A., Moilanen, J., Nikinmaa, E., & Vesala, T. (2012). Seasonal and annual variation of carbon dioxide surface
fluxes in Helsinki, Finland, in 2006-2010. Atmospheric Chemistry & Physics, 12(18).
Järvi, L., Havu, M., Ward, H. C., Bellucco, V., McFadden, J. P., Toivonen, T., ... & Grimmond, C. S. B. (2019). Spatial modeling of local-scale biogenic and
anthropogenic carbon dioxide emissions in Helsinki. Journal of Geophysical Research: Atmospheres, 124(15), 8363-8384.
Repo, A., Järvenpää, M., Kollin, J., Rasinmäki, J. & Liski, J. 2016. Yasso15 graphical user-interface manual
Ward, H. C., Järvi, L., Onomura, S., Lindberg, F., & CSB, G. (2016). SUEWS Manual: Version 2016a.
Minttu Havu15/09/2020